Since CouchDB is considered an AP (Available, Partition-Tolerant database management system), it is not really consistent (not all clients can have the same view of the data consistently) and the only way to achieve some "eventual consistency" is through replication and verification of da...

MongoDB has powerful sharding and scaling capabilities for when the data stored in the database gets so large that a single machine may not be able to store all of it. Sharding solves this problem through horizontal scaling. Mongo gives developers the ability to easily and painlessly add or remove...

Hardware requirements are very strict which makes it very hard to install and configure. Currently SAP HANA only supports hardware platforms that are Intel-based or IBM Power based. For the operating system only SUSE linux and Red Hat Enterprise linux are supported.

When a new record is written, it can trigger one or many AWS Lambda functions. With Lambda functions in Java, JavaScript, and Python and the other con of "Easy integration with other Amazon services", Lambda functions may be all you need to process the events. This is particularly useful...

DynamoDB is just a general purpose NoSQL database; hence, there are no features specific to the domain of Event Sourcing, such as event ordering or projections. As a developer, you will need to decide how to implement these.

In true AWS fashion, the documentation for DynamoDB is not top notch. While the learning curve is generally very soft and it's not hard to learn, you need to have at least some experience with cloud and database management to be able to start using DynamoDB and understand the documentation.

ConcourseDB is known to have a very holistic approach to robustness and data integrity which is reflected by it being fully ACID compliant. ConcourseDB has always been strict about making sure data is valid before allowing it into the database, and there is no way for a client to bypass those chec...

MongoDB queries can be very fast because the data is usually all in one place and can easily be retrieved in a single lookup. But this is true only when the data is truly a document. When it's trying to emulate a relational model it starts to become really slow because it may have to perform ma...

MongoDB has powerful sharding and scaling capabilities for when the data stored in the database gets so large that a single machine may not be able to store all of it. Sharding solves this problem through horizontal scaling. Mongo gives developers the ability to easily and painlessly add or remove...